Magnetic resonance (MR) imaging is a common non-invasive imaging modality useful for structural and functional imaging of living subjects. Subjects to be imaged (or scanned) are placed in or adjacent to a scanner, a magnetic field is applied, and one or more RF pulses are generated that excite and align proton spins. Following the RF pulse(s), protons relax, generating RF emissions that are detected by receivers in the scanner, and an image is generated.
MR images are dependent on a combination of intrinsic tissue properties such as spin-lattice (T1) and spin-spin (T2) relaxation times, and extrinsic properties such as imaging strategies and settings used to adjust tissue contrast in the resulting image. Images can be weighted according to T1 signal, T2 signal, or a combination thereof depending on the desired image output. Signal intensity in conventional MR images is displayed on an arbitrary scale, and thus is not adequate for direct comparisons.
Measuring maps of tissue T1 relaxation time in the human body (liver, heart, spleen, pancreas, blood, or skeletal muscle for example) using MRI scanners is a growing area. Tissue T1 indirectly probes tissue microstructure and “T1-mapping” is a powerful approach that can be used to characterize tissue in the human body in vivo. A major advantage of myocardial T1-mapping, for example, is scanner- and operator-independent quantification of structural changes that are largely independent of imaging parameters. Independence from imaging parameters allows for objective comparisons between examinations.
T1 relaxation times depend on the composition of tissues. T1 relaxation times exhibit characteristic ranges of normal values at a selected magnetic field strength. Deviation from established ranges can thus be used to quantify the effects of pathological processes and T1 changes in different organs have been associated with a variety of pathologies. In the heart for example, longitudinal relaxation time T1 changes can reveal edema (1), myocardial infarction (2) and fibrosis (3). T1-mapping may be a sensitive technique for detecting diffuse fibrosis in heart failure and valvular heart disease, which have been described by abnormal post-contrast T1 values but not by conventional late gadolinium enhanced (LGE) imaging. In the liver, T1 mapping detects the onset of fibrosis or cirrhosis more sensitively than conventional needle biopsy (4).
Pulse sequences such as modified Look-Locker inversion recovery (MOLLI) (5), shortened modified Look-Locker inversion recovery (ShMOLLI—sometimes also known as (Sh)MOLLI, although the latter can refer to MOLLI and ShMOLLI together) (6) and saturation recovery single-shot acquisition (SASHA) (7) are known for T1 mapping in the human body. Indeed, large multi-center studies (8) are now starting to use T1 mapping as an endpoint, namely a final measurement of a clinical study, experiment, clinical treatment or the like that can be used for validation, for example validation of a scientific hypothesis or determination of treatment efficacy.
One method for performing myocardial T1-mapping is the modified Look Locker inversion recovery (MOLLI) pulse sequence. With reference to FIG. 1, MOLLI merges single-shot images from three consecutive inversion-recovery (IR) epochs into one data set to give more TI samples than would otherwise be possible in one breath hold. A three-parameter fit then generates a single-slice T1 map of the myocardium.
The water T1 reflects tissue microstructure because it is effectively an indirect measure of the size of cells and the ratio of the volumes of water in the intracellular and extracellular pools. In disease, changes in tissue microstructure, such as increased interstitial volume due to edema or rupture of cell membranes after infarction, can therefore alter the water T1 value. Unfortunately, in organs such as the liver, disease progression is often associated with the formation of substantial intracellular lipid droplets, producing tissue fat fractions of up to 40% (9,10). Many current T1-mapping methods do not discriminate between water and fat when performing the inversion (or saturation) and readout. For example, MOLLI T1 values deviate substantially from the water T1 in voxels that contain a mixture of fat and water. This means that the observed T1 (T1*) may not reflect the water T1, and therefore may not reflect the expected features of the tissue microstructure: cell size, interstitial volume, etc.
Furthermore, the steady-state free precession (SSFP) readout used in MOLLI, ShMOLLI and SASHA with typical parameters at 3T, leads to opposite phase signals from fat and water. (This is illustrated for a single SSFP image in FIG. 13, and for the signals in a typical MOLLI sequence in FIGS. 5(d)-5(f), discussed below). This means that MOLLI, ShMOLLI and SASHA can significantly underestimate or overestimate the water T1 depending on the fraction of fat in a voxel. (11,12) Surprisingly, these effects can complicate the interpretation of MOLLI, ShMOLLI and SASHA results even in tissue that contains as little as 5% fat fraction.
While T1 mapping is of growing importance, fat signals can also create artifacts and image distortion, even when present in small fractions. The separation of fat and water, as well as suppression of fat signals, in homogenous and non-homogenous magnetic fields is an important issue in MRI with room for improvement. New approaches are needed to selectively measure the water T1 in tissue such as a diseased liver, in order to continue to probe tissue microstructure even when there are many lipid droplets. Accordingly, there is a need to address the aforementioned deficiencies and inadequacies.